Adaptability of Artificial Intelligence to Indigenous Knowledge of Agricultural Practices by Local Farmers in North Central, Nigeria - S. A. Busari; H. S. Banuso; Abdulrauf Tosho (International Journal of Natural Science and Engineering, 2024)
The paper was aimed at identifying the Adaptability of Artificial Intelligence (AI) to Indigenous Knowledge of Agricultural practices by Local Farmers in North central, Nigeria. Towards this end 350 traditional agricultural consisting of 238 males and 112 females practitioners were selected across the states of the region, including the Federal Capital Territory (FCT), by means of sheer random sampling technique three research questions were raised concerning the farmers attitude towards the integration of AI potential impacts on the sustainability of their agricultural practices. The research instrument was titled “Attitude of indigenous agricultural practitioners to the adaption of Artificial Intelligence (AI) questionnaire”, Which was structured. Results indicated that, although the agricultural practitioners had positive attitude towards AI, there is a critical need for culturally sensitive approaches. The study also revealed the importance of tailoring AI solutions that align with the unique needs and values of various North Central Nigeria indigenous communities. Furthermore, there should be collaborative efforts among technologists, anthropologists and local agricultural practitioners for the purpose of designing AI systems that enhance indigenous knowledge in agricultural practices. It was recommended that the government should encourage active involvement of indigenous agricultural practitioners in the design, implementation and evaluations of AI integration initiatives, so as to ensure that AI solutions align with local needs and preference within the cultural contexts. Furthermore, the government should carry out robust monitoring and evaluation mechanisms to assess the impact of AI integration on indigenous knowledge systems, perceptions and sustainability. These include collecting relevant data, soliciting feedback from stakeholders and adapting strategies based on findings.